**This has been replaced with the music analysis now built in to music_monitor [here](https://github.com/benarmstead/music_monitor).**

workflow
workflow

Generates graphs on users music listening habits.

This is meant for processing and analysing the data from my cmus-music-monitor shell script.

However, this program will work on any CSV formatted:

<Title>, <Artist>, <Album>, <Genre>, <Song Length>, <Track number>, <Year>, <Play date>, <Play time>, <Volume>

(Its also very easy to modify it to take data from another format if you know python).

Future goals

  • Move to a database format rather than CSV (need to convert cmus-music-monitor to this first though).
  • Generate predicted usage and spot patterns with machine learning.
  • Implement more features such as different ways of viewing graphs etc.

Installation

git clone https://github.com/benarmstead/music-grapher

cd music-grapher/src

Running

python3 main.py /path/to/your.csv

Features

Feature Text Explinations

  • Ability to genearte a video of a pie chart changing over time based on your music listening habits.

(Cannot demonstrate here due to being unable to remove band names from my example video)

(It is essentially Most Played Artists however animated over time)

Feature Image Examples

Start

Start

Menu

Most Played Songs

Most Played Songs

Most Played Artists

Most Played Artists

Avg songs p/day

Avg songs p/day

Most Played Days

Most Played Days

Unique songs played

Unique songs played

Ben Armstead
Ben Armstead
Computer Science Undergraduate (Lancaster University)

I enjoy free software programming and learning about Linux.

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